DummyJSON MCP for AI. Mock all data flows without a backend setup.
Works with every AI agent you already use
…and any MCP-compatible client








Connect to your AI in seconds.
DummyJSON MCP gives you instant access to a massive set of simulated data for testing any API flow. Need to mock up an e-commerce checkout, simulate user logins, or test content management? This single connector lets your AI agent interact with structured dummy records—everything from products and shopping carts to posts, comments, and recipes—so you can build and prove your application logic without ever touching a real backend.
What your AI can do
Add cart
Creates a brand new shopping cart record for a user.
Add comment
Adds a comment to an existing post.
Add post
Creates entirely new content posts on the platform.
Authenticate users, retrieve profiles, and manage user records like adding or deleting accounts.
List, search, update, and delete product details, simulating an entire e-commerce lifecycle.
Create, read, and modify posts, comments, recipes, and todo items to test content platform logic.
Manage the entire shopping cart workflow by listing carts, adding items, updating quantities, or deleting them.
Narrow down large sets of data—like users, posts, or products—using specific criteria to find exactly what you need.
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DummyJSON: 61 Tools for API Simulation
These tools allow your AI agent to perform every data operation imaginable, including adding, getting, updating, deleting, and searching across products, users, posts, recipes, and more.
Make your AI actually useful.
Add this MCP to Claude, Cursor, or Windsurf and your AI stops guessing. It gets real tools to look things up, take action, and handle the stuff you keep doing by hand.
Start using DummyJSON on VinkiusAdd Cart
Creates a brand new shopping cart record for a user.
Add Comment
Adds a comment to an existing post.
Add Post
Creates entirely new content posts on the platform.
Add Product
Simulates adding a completely new product to the catalog.
Add Recipe
Adds a new recipe record, including ingredients and instructions.
Add Todo
Creates a fresh task or todo item in the user's list.
Add User
Registers a new dummy user account into the system.
Delete Cart
Removes an entire shopping cart record from the system.
Delete Comment
Deletes a comment that was previously posted on a piece of content.
Delete Post
Permanently removes a published post from the platform.
Delete Product
Simulates removing a product entry from the catalog.
Delete Recipe
Removes an entire recipe from the database.
Delete Todo
Marks or deletes a specific todo item that was previously created.
Delete User
Deactivates or removes a user account from the system.
Filter Users
Narrows down the list of users by searching against provided key/value pairs.
Get Cart
Retrieves all details for a single shopping cart using its unique ID.
Get Comment
Retrieves the full content of one specific comment by its ID number.
Get Comments By Post
Pulls all comments that belong to a single, specified post.
Auth Get Me
Checks and returns the profile information of the currently logged-in user.
Get Post Comments
Gets a list of all comments associated with a given post ID.
Get Post
Retrieves the full details of one specific article or post by its ID.
Get Posts By User
Finds and lists all posts that were written by a particular user ID.
Get Product
Retrieves the full details for one specific product using its unique identifier.
Get Products By Category
Lists all products that fall under a specified category, like 'Electronics' or 'Apparel'.
Get Quote
Retrieves the text and author for one random quote by its ID.
Get Random Quote
Pulls a completely random quote from the entire dataset.
Get Random Quotes
Retrieves up to ten unique, randomly selected quotes for filler content.
Get Random Todo
Presents a random task from the user's todo list.
Get Recipe
Gets all details for one recipe by its unique ID.
Get Recipes By Meal Type
Finds and lists recipes suitable for a specific meal, like 'Dinner' or 'Breakfast'.
Get Recipes By Tag
Retrieves all recipes that share a common tag, such as 'vegan' or 'quick-prep'.
Get Todo
Gets the details for one specific todo item by its ID.
Get User Carts
Lists all shopping carts that are associated with a specific user account.
Get User Posts
Retrieves all posts written by a given user ID.
Get User Todos
Gets a list of todos that belong to a specific user account.
Get User
Retrieves a single user's complete profile using their unique ID.
List Carts
Retrieves a list of every shopping cart available in the system.
List Categories
Gets a list of all defined product categories by name.
List Category List
Retrieves just the names of every available product category.
List Comments
Gets a list of every comment ever posted on the platform.
List Post Tags
Retrieves a complete list of all post tags used across content.
List Posts
Gets a comprehensive list of every single post published on the platform.
List Products
Retrieves a full listing of all products currently in the catalog.
List Quotes
Gets every quote record that exists in the database.
List Recipe Tags
Retrieves a complete list of all tags used to categorize recipes.
List Recipes
Gets every recipe record available in the system.
List Todos
Retrieves a complete list of all todo items stored by users.
List Users
Get all users
Auth Login
Simulates a user logging in and receiving dummy access tokens (JWT).
Auth Refresh Token
Extends an active session by generating new JWT tokens using a refresh token.
Search Posts
Searches the entire post database using keywords or filters.
Search Products
Searches the product catalog for specific items by name or description.
Search Recipes
Searches recipes using keywords, like 'chicken' or 'spicy'.
Search Users
Finds users by searching their name or email address.
Update Cart
Modifies items within a shopping cart, like changing quantity or removing an item.
Update Comment
Edits the text of a comment that was previously posted.
Update Post
Changes the content and details of an existing published post.
Update Product
Updates product information, such as changing pricing or descriptions.
Update Recipe
Edits the ingredients or instructions for an existing recipe.
Update Todo
Changes the status, description, or assignee of a todo item.
Update User
Modifies details on a user profile, like changing an email or name.
Security and governance baked right in.
Pick your AI client below to get set up. Just create a Vinkius account, subscribe, and you're instantly up and running. We handle the entire backend infrastructure, delivering out-of-the-box support for HTTPS Streamable, SSE, and OAuth2—zero messy routing required.
Choose How to Get Started
Build a custom MCP for your own tools, or connect a ready-made integration from our catalog.
Build Your Own
Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.
- Import from OpenAPI, Swagger, or YAML specs
- Create Agent Skills with progressive disclosure
- Deploy to edge with MCPFusion framework
- Built in DLP, auth, and compliance on every call
- Real time usage dashboard and cost metering
- Publish to catalog or keep private
Make Your AI Do More
Start with DummyJSON, then connect any of our 5,100+ other servers whenever your AI needs more. One click, no limits.
- Use this MCP plus 5,100+ others, all in one place
- Add new capabilities to your AI anytime you want
- Every connection is secured and compliant automatically
- Track usage and costs across all your servers
- Works with Claude, ChatGPT, Cursor, and more
- New servers added to the catalog every week
VINKIUS INFRASTRUCTURE
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Zero-Trust Proxy
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Token Compression
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Works with Claude, ChatGPT, Cursor, and more
The Model Context Protocol standardizes how applications expose capabilities to LLMs. Instead of operating in isolation, your AI gains direct access to external platforms, live data, and real-world actions through secure, standardized connections.
This connection provides 61 powerful capabilities that interface natively with Claude, ChatGPT, Cursor, and other compatible AI platforms. No middleware. No custom integration required.
Manually testing every content interaction feels like a full-time job.
Right now, if your team wants to test how a comment system works, someone has to manually create a post in the CMS, then log in as User A and add a comment. Then they have to switch accounts, log in as User B, and repeat the process. That's copy-pasting IDs and clicking through three different tabs just to see if the relationship between posts and comments holds up.
With this MCP, your agent handles all that complexity. You tell it: 'Show me a post, then add two comments for that post from two different users.' The data instantly appears, fully connected and ready for you to check against your UI logic. It just makes the whole process reliable.
The DummyJSON MCP delivers full product lifecycle simulation.
Before this, if a developer wanted to test adding a new item, they had to wait for an admin to manually add a fake product record in the database. Testing changes meant someone having to go into the backend dashboard and run `update_product` manually just so everyone could see it.
Now you call `add_product` directly from your agent. The data appears instantly, complete with all the necessary fields. Your development cycle speeds up because you don't have to wait on manual steps anymore.
What your AI can actually do with this
Building an app shouldn't mean setting up 10 different mock databases just to test the frontend. This MCP lets you simulate real-world data interactions directly through your AI client. You connect it via Vinkius, giving your agent immediate access to everything from product catalogs and user profiles to full content feeds.
Want to build a checkout flow? Your agent can list products, add them to a cart, and then simulate the final purchase process. Need to test a social media feed? You can generate posts, comments, and even users, all within the same session. This means you spend zero time wrestling with backend setup and 100% of your time testing how your UI handles data—whether it's an error state, a successful update, or just pulling random content for quick prototyping.
019e5d13-ebb1-72b9-b383-ab13c36ee222 Here's how it actually works
The bottom line is, your AI client treats this MCP like a live API endpoint for testing purposes.
Subscribe to the MCP via Vinkius and connect your preferred AI client.
(Optional) Provide any necessary credentials if a specific implementation requires a token for simulation.
Tell your agent exactly what data you need—like 'Show me three products in the electronics category' or 'Add a new post about remote work.' The MCP executes that request against its dummy database.
Who is this actually for?
Frontend engineers and QA specialists who get stuck waiting for the backend team to finish their database setup. It's also perfect for AI researchers needing a stable, predictable sandbox to test tool-calling logic without external dependencies.
Building components that need data—like product cards or user dashboards—and needs immediate mock data to start coding the UI.
Writing test scripts that must hit edge cases, such as trying to update a non-existent record or simulating an auth token expiration.
Training agents on complex multi-step workflows, like 'User logs in, views products, adds items to cart, and then gets their profile.'
What Changes When You Connect
You can test e-commerce logic end-to-end. Use the list_products tool to pull an inventory, then use add_cart and update_cart to simulate adding items before verifying checkout status.
Build reliable social features without worrying about users. Test commenting by calling get_post_comments and simulating new input with add_comment, ensuring your UI handles multiple authors correctly.
Rapidly mock user experiences. Need a profile page? Use auth_login to simulate authentication, then use get_user to pull the necessary details for display, all in one flow.
Handle complex content types easily. Whether you are writing about food or tech, you can manage recipes using tools like list_recipes and create new entries with add_recipe, ensuring your UI adapts to different data structures.
Test database writes safely. You need to verify that a user can delete old content? Use delete_post and then check the status via get_posts_by_user. It's safe, predictable dummy data every time.
See it in action
Building a Content Management System (CMS)
A developer needs to build an admin panel where content creators can update articles. They use the agent to first call get_post to view the current draft, then call update_post with new text, and finally run list_post_tags to ensure all proper tags are available for selection.
Testing User Registration Flow
A QA engineer needs to verify that a user's profile picture loads correctly after signup. They use the agent to call add_user to create a test account, then immediately call get_user with the new ID to confirm all profile fields are populated.
Simulating an E-commerce Checkout
A frontend developer needs to mock the entire purchasing journey. The agent first calls list_products, then uses add_cart and update_product (to check pricing), simulating adding multiple items before calling get_user_carts to confirm the cart is linked.
Creating a To-Do List App
A researcher wants to test how an agent handles task management. They use the agent to call add_todo, then simulate marking it complete by calling update_todo, and finally retrieving the whole set using get_user_todos.
The honest tradeoffs
Assuming data exists
Telling your agent, 'Get me the comments on Post 45.' If that post ID was deleted in a previous test run, the call fails and breaks your whole workflow.
Always check first. Use get_post with an ID before trying to get associated content. Then use list_comments or get_comments_by_post to verify the comments actually exist.
Mixing data sources
Trying to pull a recipe's ingredients list and then using those ingredient names to search for products in an e-commerce catalog.
Keep domains separate. Use get_recipe for the food data, and use search_products only when you are sure the product is related. Don't mix them up.
Ignoring authentication status
Calling add_user or delete_cart without first simulating a login, assuming the system knows who made the change.
Always start by running auth_login to establish a session. Then use get_me or pass the resulting token/ID into all subsequent write operations.
When It Fits, When It Doesn't
Use this MCP if your primary job is testing data flows and UI logic—you need predictable, repeatable data for any scenario (e-commerce, social media, etc.). It’s perfect when you can't wait for a backend team or just want to prove out an API contract. Don't use it if your goal is to actually save this data somewhere permanent; this MCP only simulates operations. If you need real user input, payment gateway integration, or database writes that affect production records, you must connect to the actual service using its dedicated APIs instead.
Questions you might have
How do I test a full user account lifecycle using DummyJSON MCP? +
Start by calling auth_login to get tokens. Then use add_user to create a new profile, and finally get_user with the ID to confirm all data fields were set up correctly.
Can I mock product searches in DummyJSON MCP? +
Yes. Use the search_products tool. It lets your agent filter products by keywords, simulating how a live e-commerce site finds items for a user.
What if I want to update an item in my cart? Do I use add_cart? +
No. Use update_cart. The add_cart tool is only for creating a brand new, empty shopping cart record.
Does DummyJSON MCP help me write posts and comments at the same time? +
Yes. You can chain these tools: use add_post first to create content, and then immediately call add_comment using the ID from that new post.
How do I get a list of all categories for products? +
Use list_categories. This tool returns every category object defined in the dummy data, giving you a full list of available labels to test against.
What happens if I need to extend a session using `auth_refresh_token`? +
Yes, you can refresh your session token. This allows your agent to continue making authenticated calls without needing to re-run the initial login process. It's essential for simulating long user interactions where tokens expire.
How do I test a complex transaction by combining tools like `add_product` and `update_user`? +
You chain multiple tool calls sequentially in your prompt. The AI agent executes them one after the other, simulating a full data flow. This lets you verify that different mocked records interact correctly within your application logic.
Can `filter_users` narrow down results based on multiple key-value criteria? +
Yes, it accepts filters by providing multiple key and value pairs in a single request. This makes it easy to test highly specific search scenarios that require filtering across several user attributes simultaneously.
How can I retrieve a list of all products with a specific limit? +
You can use the list_products tool and provide the limit parameter to control the number of results returned by the API.
Is it possible to simulate adding a product to the database? +
Yes! Use the add_product tool. Note that this is a simulation; the API will return the new product object with an ID, but it won't be permanently stored.
How do I check the carts belonging to a specific user? +
Simply use the get_user_carts tool and provide the userId. The agent will return all shopping carts associated with that specific user ID.
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